Remote estimation is a crucial element of real time monitoring of a stochastic process. While most of the existing works have concentrated on obtaining optimal sampling strategies, motivated by malicious attacks on cyber-physical systems, we model sensing under surveillance as a game between an attacker and a defender. This introduces strategic elements to conventional remote estimation problems. Additionally, inspired by increasing detection capabilities, we model an element of information leakage for each player. Parameterizing the game in terms of uncertainty on each side, information leakage, and cost of sampling, we consider the Stackelberg Equilibrium (SE) concept where one of the players acts as the leader and the other one as the follower. By focusing our attention on stationary probabilistic sampling policies, we characterize the SE of this game and provide simulations to show the efficacy of our results.

翻译：远程估计是随机过程实时监测的关键环节。现有研究大多集中于获取最优采样策略，而受网络物理系统恶意攻击的启发，我们将监控下的感知建模为攻击者与防御者之间的博弈。这为传统远程估计问题引入了策略性要素。此外，受日益增强的检测能力启发，我们为每位博弈者构建了信息泄露模型。通过以各方不确定性、信息泄露及采样成本为参数构建博弈模型，我们采用斯塔克尔伯格均衡（SE）概念进行分析，其中一方作为领导者，另一方作为跟随者。通过聚焦于稳态概率采样策略，我们刻画了该博弈的SE特征，并通过仿真验证了所提结果的有效性。